Before the advent of molecular phylogenetics, species concepts in the downy mildews, an economically important group of obligate biotrophic oomycete pathogens, have mostly been based upon host range and morphology. While molecular phylogenetic studies have confirmed a narrow host range for many downy mildew species, others, like Pseudoperonospora cubensis affect even different genera. Although often morphological differences were found for new, phylogenetically distinct species, uncertainty prevails regarding their host ranges, especially regarding related plants that have been reported as downy mildew hosts, but were not included in the phylogenetic studies. In these cases, the basis for deciding if the divergence in some morphological characters can be deemed sufficient for designation as separate species is uncertain, as observed morphological divergence could be due to different host matrices colonised. The broad host range of P. cubensis (ca. 60 host species) renders this pathogen an ideal model organism for the investigation of morphological variations in relation to the host matrix and to evaluate which characteristics are best indicators for conspecificity or distinctiveness. On the basis of twelve morphological characterisitcs and a set of twelve cucurbits from five different Cucurbitaceae tribes, including the two species, Cyclanthera pedata and Thladiantha dubia, hitherto not reported as hosts of P. cubensis, a significant influence of the host matrix on pathogen morphology was found. Given the high intraspecific variation of some characteristics, also their plasticity has to be taken into account. The implications for morphological species determination and the confidence limits of morphological characteristics are discussed. For species delimitations in Pseudoperonospora it is shown that the ratio of the height of the first ramification to the sporangiophore length, ratio of the longer to the shorter ultimate branchlet, and especially the length and width of sporangia, as well as, with some reservations, their ratio, are the most suitable characteristics for species delimitation.

Smut fungi are well-suited to investigate the ecology and evolution of plant pathogens, as they are strictly biotrophic, yet cultivable on media. Here we report the genome sequence of Melanopsichium pennsylvanicum, closely related to Ustilago maydis and other Poaceae-infecting smuts, but parasitic to a dicot plant. To explore the evolutionary patterns resulting from host adaptation after this huge host jump, the genome of M. pennsylvanicum was sequenced and compared to the genomes of Ustilago maydis, Sporisorium reilianum, and Ustilago hordei. While all four genomes had a similar completeness in CEGMA analyses, gene absence was highest in M. pennsylvanicum, and most pronounced in putative secreted proteins, which are often considered as effector candidates. In contrast, the amount of private genes was similar among the species, highlighting that gene loss rather than gene gain is the hallmark of adaptation after the host jump to the dicot host. Our analyses revealed a trend of putative effectors to be next to another putative effector, but the majority of these are not in clusters and thus the focus on pathogenicity clusters might not be appropriate for all smut genomes. Positive selection studies revealed that M. pennsylvanicum has the highest number and proportion of genes under positive selection. In general, putative effectors showed a higher proportion of positively selected genes than non-effector candidates. The 248 putative secreted effectors found in all four smut genomes might constitute a core set needed for pathogenicity, while those 92 that are found in all grass-parasitic smuts, but have no ortholog in M. pennsylvanicum might constitute a set of effectors important for successful colonization of grass hosts.

High-throughput metabarcoding studies on fungi and other eukaryotic microorganisms are rapidly becoming more frequent and more complex, requiring researchers to handle ever increasing amounts of raw sequence data. Here, we provide a flexible pipeline for pruning and analyzing fungal barcode (ITS rDNA) data generated as paired-end reads on Illumina MiSeq sequencers. The pipeline presented includes specific steps fine-tuned for ITS, that are mostly missing from pipelines developed for prokaryotes. It (1) employs state of the art programs and follows best practices in fungal high-throughput metabarcoding; (2) consists of modules and scripts easily modifiable by the user to ensure maximum flexibility with regard to specific needs of a project or future methodological developments; and (3) is straightforward to use, also in classroom settings. We provide detailed descriptions and revision techniques for each step, thus giving the user maximum control over data treatment and avoiding a black-box approach. Employing this pipeline will improve and speed up the tedious and error-prone process of cleaning fungal Illumina metabarcoding data.